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Publisher ‏ : ‎ Chapman and Hall/CRC; 1st edition (December 14, 2023)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 444 pages
ISBN-10 ‏ : ‎ 1032314656
ISBN-13 ‏ : ‎ 978-1032314655
Item Weight ‏ : ‎ 13.45 pounds
Dimensions ‏ : ‎ 7 x 1.19 x 10 inches

In this post, we will delve into the world of autonomous experimentation and its various methods and applications as discussed in the book “Methods and Applications of Autonomous Experimentation” published by Chapman & Hall/CRC Computational Science.

Autonomous experimentation refers to the use of intelligent systems and algorithms to design, conduct, and analyze experiments without human intervention. This book provides a comprehensive overview of the latest advancements in this field, covering topics such as automated design of experiments, autonomous data collection, and machine learning for experiment optimization.

Some of the key methods discussed in the book include Bayesian optimization, reinforcement learning, and active learning, which enable autonomous systems to efficiently explore complex experimental spaces and optimize outcomes. These methods are applied in a wide range of fields, including drug discovery, materials science, and industrial process optimization.

The applications of autonomous experimentation are vast and impactful, offering new opportunities for accelerating scientific discovery and innovation. By automating the experimental process, researchers can uncover new insights, identify optimal conditions, and make data-driven decisions faster and more efficiently than ever before.

Overall, “Methods and Applications of Autonomous Experimentation” provides a valuable resource for researchers, engineers, and data scientists interested in harnessing the power of autonomous systems to revolutionize the way experiments are conducted. Whether you are new to the field or a seasoned practitioner, this book offers valuable insights and practical guidance for leveraging autonomous experimentation in your own work.
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